findmu: Determine equidistant means of trinormal ROC data simulation

In trinROC: Statistical Tests for Assessing Trinormal ROC Data

Determine equidistant means of trinormal ROC data simulation

Description

A function that computes the equidistant means muy and muz for a specific mux. The VUS as well as the set of standard errors are given as arguments to the function.

Usage

findmu(mux = 0, sdx = 1, sdy = 1, sdz = 1, VUS = 1/6, step = 0.001)

Arguments

mux	The numeric mean of the healthy class. Default is zero.
sdx, sdy, sdz	The numeric standard errors of the healthy, intermediate and diseased class, for which the according means have to be determined given a specifiv VUS.
VUS	The Volume Under the Surface. A numeric value between 1/6 and 1. Default is 1/6.
step	A numeric indicating the step size each iteration takes in order to find the closest set of means. Default set to 0.001.

Details

Defaults are: VUS = 1/6, standard errors for all three classes equal 1. The searching algorithm is stepwise increasing the differences muy-mux and muz-mux according to the variable step. The algorithm stops when the computed VUS exceeds the preferred VUS. The according parameters mux, muy, muz are returned with the computed VUS.

Remark: The bigger VUS and the smaller step is chosen, the longer the computation lasts.

Value

A data frame with the following components:

mux	The initial mean of the healthy class
muy	The mean of the intermediate class computed for the specified VUS.
muz	The mean of the diseased class computed for the specified VUS.
VUS	The VUS computed for mux, muy and muz.

Examples

# find equidistant means with mux=2.7 and VUS = 0.45:
findmu(mux = 2.7, VUS = 0.45)
# specify standard errors:
findmu(mux = 2.7, sdx = 1.1, sdy = 1.3, sdz = 1.5, VUS = 0.45)

trinROC documentation built on Oct. 29, 2022, 1:12 a.m.